Metadata-Version: 2.4
Name: sara_engine
Version: 0.1.3
Classifier: Programming Language :: Rust
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: numpy
Summary: A biologically plausible, lightweight Spiking Neural Network engine (CPU-only, No-BP).
Author-email: Your Name <your.email@example.com>
Requires-Python: >=3.8
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Homepage, https://github.com/yourusername/sara_engine

# SARA Engine (Liquid Harmony)

**SARA (Spiking Advanced Recursive Architecture)** is a next-generation AI engine (SNN-based) that mimics the biological brain's "power efficiency, event-driven processing, and self-organization."

It completely eliminates the "backpropagation (BP)" and "matrix operations" that modern deep learning (ANNs) rely on, achieving advanced recognition and learning capabilities using **only sparse spike communication**.

It operates on CPU only, without using any GPU.

Current Version: **v0.1.2**

## Features

* **No Backpropagation**: Learns without error backpropagation, using local learning rules (Momentum Delta) and reservoir computing.
* **CPU Only & Lightweight**: Does not require expensive GPU resources. Runs fast on standard CPU environments.
* **Multi-Scale True Liquid Reservoir**: Three parallel reservoir layers with different temporal characteristics (Decay), with recurrent connections within each layer. Achieves short-term memory using information "echo."
* **Rust Acceleration**: Core computation logic is written in Rust for high performance.

## Installation  
  
```bash
pip install sara-engine
```  
Quick Start  
  
```bash
from sara_engine import SaraGPT

# Initialize the brain
brain = SaraGPT(sdr_size=1024)

# Create an input pattern (SDR)
input_sdr = brain.encoder.encode("Hello SARA")

# Think (Forward pass)
output_sdr, spikes = brain.forward_step(input_sdr)

print(f"Output Active Neurons: {len(output_sdr)}")
```
  
License  
MIT License  
